Prognostic Value of Germline Copy Number Variants and Environmental Exposures in Non-small Cell Lung Cancer

Germline copy number variant (gCNV) has been studied as a genetic determinant for prognosis of several types of cancer, but little is known about how it affects non-small cell lung cancer (NSCLC) prognosis. We aimed to develop a prognostic nomogram for NSCLC based on gCNVs. Promising gCNVs that are associated with overall survival (OS) of NSCLC were sorted by analyzing the TCGA data and were validated in a small Chinese population. Then the successfully verified gCNVs were determined in a training cohort (n = 570) to develop a prognostic nomogram, and in a validation cohort (n = 465) to validate the nomogram. Thirty-five OS-related gCNVs were sorted and were reduced to 15 predictors by the Lasso regression analysis. Of them, only CNVR395.1 and CNVR2239.1 were confirmed to be associated with OS of NSCLC in the Chinese population. High polygenic risk score (PRS), which was calculated by the hazard effects of CNVR395.1 and CNVR2239.1, exerted a significantly higher death rate in the training cohort (HR = 1.41, 95%CI: 1.16-1.74) and validation cohort (HR = 1.42, 95%CI: 1.13-1.77) than low PRS. The nomogram incorporating PRS and surrounding factors, achieved admissible concordance indexes of 0.678 (95%CI: 0.664-0.693) and 0.686 (95%CI: 0.670-0.702) in predicting OS in the training and validation cohorts, respectively, and had well-fitted calibration curves. Moreover, an interaction between PRS and asbestos exposure was observed on affecting OS (P-interaction = 0.042). Our analysis developed a nomogram that achieved an admissible prediction of NSCLC survival, which would be beneficial to the personalized intervention of NSCLC.

Automated summary

This study developed a prognostic nomogram for NSCLC based on gCNVs and validated two gCNVs associated with NSCLC overall survival in a Chinese population. The high polygenic risk score (PRS) calculated from CNVR395.1 and CNVR2239.1 showed significantly higher death rates in both the training and validation cohorts. The nomogram, incorporating PRS and other factors, demonstrated good predictive performance and calibration in predicting NSCLC survival, with an observed interaction between PRS and asbestos exposure.